Operations | Monitoring | ITSM | DevOps | Cloud

When CFOs talk about AI budgets, they tend to describe it the same way: it’s a black box, offering little or no transparency. The bill arrives at the end of the month, it’s bigger than last month, and nobody can really explain why. Meanwhile, engineering keeps asking to raise the token budget. I think that framing undersells what’s actually happening out there. If the black box is the bill, the Pandora’s box is what you opened when you brought AI into the company.

Generative AI ROI measures the financial return on generative AI investments relative to their total cost. Benchmarks diverge sharply: Google Cloud's 2025 study found 74% of enterprises see ROI within the first year, while MIT's NANDA initiative found 95% of pilots deliver no measurable P&L impact. The difference is not the AI. It is whether the organization can actually measure cost and outcome at the use case level.

There’s an S3 charge that stays invisible in a normal storage cost review. AWS bills S3 object tags per tag, per hour, so the cost scales with how many objects you have, not how much data you store. It gets its own line item, which is easy to miss when you’re scanning storage spend. It can sneak up on you. Tags get added in a dev environment to drive lifecycle rules, where object counts are small and the cost is nothing.

The GPU cloud conversation over the last three years has been almost entirely captured by AI. Marketing pages talk about training, inference, and foundation models. Vendor announcements focus on which NVIDIA card fits which LLM. Reference customers are AI companies. The infrastructure decisions being made in the market are shaped by AI's specific requirements - high VRAM, fast interconnect, FP8 support, continuous utilization patterns.

Your ISP tells you your connection is up 99.9% of the time. Your users tell you the MS Teams video calls keep freezing. Both can be true at once, and that gap is exactly why you need to monitor Internet uptime yourself instead of taking your provider's word for it. This article covers what Internet uptime actually means, how to calculate it, what a good internet uptime SLA looks like, and how to monitor internet uptime with your own data so you're not stuck relying on your ISP's version of events.

Teams supporting user-facing applications rely on session replays to understand user friction. But resolving an issue or improving the user experience takes more than watching a replay. Engineers, product managers, and designers first need to find the right sessions to investigate, then quickly learn what happened at the key moments. Once they’ve investigated a replay, they need to share what they found across product, design, support, and engineering so that the right teams can act.

On the morning of August 5, 2026, a major AI provider went dark for roughly seven and a half hours, and thousands of engineering teams learned in real time what an AI provider outage actually costs them. Anthropic's Claude models returned elevated error rates and failed API requests starting around 3:00 AM Eastern, and applications that quietly route user traffic through a large language model suddenly had no model to route to. Chatbots stopped answering. Summarization pipelines stalled.

Our iPhones now have the capability to take amazing, high-quality photos and videos, but they can quickly eat up your storage if you don’t know how to reduce photo size on iPhone, or how to compress a photo on iPhone. If your cloud storage runs out, you can use the methods in this article to free up the space on your phone or back up your photos on another private alternative to iCloud Photos, like Internxt Drive and Photos.